Data Engineer - Scala

About us

We are champions of rail, inspired to build a greener, more sustainable future of travel. Trainline enables millions of travellers to find and book the best value tickets across carriers, fares, and journey options through our highly rated mobile app, website, and B2B partner channels.

Great journeys start with Trainline 🚄

Now Europe’s number 1 downloaded rail app, with over 125 million monthly visits and £5.9 billion in annual ticket sales, we collaborate with 270+ rail and coach companies in over 40 countries. We want to create a world where travel is as simple, seamless, eco-friendly and affordable as it should be.

Today, we re a FTSE 250 company driven by our incredible team of over 1,000 Train liners from 50+ nationalities, based across London, Paris, Barcelona, Milan, Edinburgh and Madrid. With our focus on growth in the UK and Europe, now is the perfect time to join us on this high-speed journey.

Data Engineering is essential to how we unlock the value of data  mission is to liberate Trainline data and delight customers with great data products built on a frictionless, modern data platform. Our data products include machine learning models that add real value to the customer journey, streaming data applications that personalise the customer experience in real time, dashboards that drive deep business and customer insight and intuitive and efficient data marts and metrics built on our modern Data Lakehouse.

As a Data Engineer, you will be part of a cross-functional Data Platform team working alongside data engineers, data scientists, machine learning engineers and BI engineers. Our data product teams are deeply embedded in the business so your work will have high impact by either driving key business decisions, providing deep customer insights or by adding intelligent machine learning experiences right in the core of our customer journeys.

We use an agile delivery playbook that encourages incremental and iterative delivery, aims to release value early and often, measure the impact of work and using hypotheses to ensure we are solving real customer problems. Our Data Platform is a modern, cloud-native, lake house using best-of-breed technologies and partners, all based on the AWS public cloud.

We empower our Data teams and give engineers high levels of autonomy and freedom to innovate. We encourage continuous learning with clear career progression plans, innovation/hack days and training opportunities and budget.

• Use cutting-edge Data technology to deliver world-class data products using a combination of streaming technologies, machine learning and automated data pipelines.
• Work in self-organised, cross-functional data teams alongside machine learning engineers, BI engineers and product managers.
• Drive continuous improvement to the software engineering and agile working practices of the team.
• Contribute to the Technical / Architecture direction of the team.

• Thrive in a diverse, open and collaborative environment where impact is as valuable as technical skill.
• Have proficient knowledge of Scala and the JVM ecosystem.
• Possess familiarity of functional programming paradigms and a willingness to adopt other languages (not only JVM languages).
• Have consistent background in software development in high volume environments.
• Have a pragmatic and open-minded approach to achieving outcomes in the simplest way possible.
• Have worked with stream processing technologies (i.e. Apache Kafka).
• Have experience with AWS services especially Elasticache & ECS.
• Are passionate about software quality, Dev Ops (i.e. Terraform) and automation.
• Work well in lean, agile, cross-functional product teams using Scrum and Kanban practices.
• Are a good communicator and comfortable with presenting ideas and outputs to technical and non-technical stakeholders.

Enjoy fantastic perks like private healthcare & dental insurance, a generous work from abroad policy, 2-for-1 share purchase plans, an EV Scheme to further reduce carbon emissions, extra festive time off, and excellent family-friendly benefits.

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